Why Scaling by the Square Root of Dimensions Matters in Attention | Transformers in Deep Learning

Why do we divide by the square root of the key dimensions in Scaled Dot-Product Attention? 🤔 In this video, we dive deep into the intuition and mathematics behind this crucial step. Understand: 🔹 How scaling prevents extreme attention scores. 🔹 The impact of dimensionality on softmax. 🔹 Why this scaling makes models more stable and efficient. If you’ve ever wondered about this subtle yet vital detail, this video is for you, where we go in-depth into why this scaling is so important for the stability in training of the model. 📕 NOTES: https://github.com/Coding-Lane/Transformer-notes/bl…